Torsten Wilhelm

An Approach to Multi-modal Human-Machine Interaction for Intelligent Service Robots

Abstract The paper describes a multi-modal scheme for human–robot interaction suited for a wide range of intelligent service robot applications. Operating in un-engineered, cluttered, and crowded environments, such robots have to be able to actively contact potential users in their surroundings and to offer their services in an appropriate manner. Starting from a real application scenario, the usage of a robot as mobile information kiosk in a home store, some reliable methods for vision-based interaction, sound analysis and speech output have been developed. These methods are integrated into a prototypical interaction cycle that can be assumed as a general approach to human–machine interaction. Experimental results demonstrate the strengths and weaknesses of the proposed methods.

A Multi-Modal System for Tracking and Analyzing Faces on a Mobile Robot

Abstract This paper describes a user detection system which employs a saliency system working on an omnidirectional camera delivering a rough and fast estimate of the position of a potential user. It consists of a vision (skin color) and a sonar based component, which are combined to make the estimate more reliable. To make the skin color detection robust under varying illumination conditions, it is supplied with an automatic white balance algorithm. The active vision head looks continuously in the direction of the salient region. Thus, a high resolution image can be grabbed and analyzed with a face detector.

Classification of face images for gender, age, facial expression, and identity

In this paper we compare two models for extracting features from face images and several neural classifiers for their applicability to classify gender, age, facial expression, and identity. These models are i) a description of face images by their projection on independent base images and ii) an Active Appearance Model which describes the shape and grey value variations of the face images. The extracted feature vectors are classified with Nearest Neighbor, MLP, RBF and LVQ networks, and classification results are compared.

Contribution to vision-based localization, tracking and navigation methods for an interactive mobile service-robot

Presents vision-based robot navigation and user localization techniques of our long-term research project PERSES (personal service system), which aims to develop an interactive mobile shopping assistant that allows a continuous and intuitively understandable interaction with customers in a home store. Against this background, the paper describes a number of new or improved approaches, addressing challenges arising from the characteristics of the operation area, and from the need to continuously interact with users in a complex environment. With our approaches to vision-based or visually-controlled map building, self-localization and navigation as well as user localization and tracking, we want to make a contribution to the real-world suitability of interactive mobile service-robots in non-trivial application areas and demanding human-robot interaction scenarios.

Gesichtsanalyse für die intuitive Mensch-Roboter-Interaktion

Der Beitrag beschreibt Verfahren zur visuellen Gesichtsanalyse im Kontext der Mensch-Roboter-Interaktion. Dabei besteht das mittelfristige Ziel darin, neben der Identifizierung des aktuell angemeldeten Nutzers auch dessen Geschlecht, das Alter sowie den Gesichtsausdruck zu ermitteln und damit uber moglichst reichhaltige Statusinformationen uber den menschlichen Interaktionspartner zu verfugen, um seitens des Roboters die Dialogfuhrung entsprechend anpassen zu konnen. Um diese Informationen aus dem Gesichtsbild zu extrahieren, werden die Verfahren Elastic Graph Matching, Independent Component Analysis sowie Active Appearance Models in Verbindung mit verschiedenen Klassifikatoren vergleichend untersucht, wobei hier zunachst der Schwerpunkt auf der Personenidentifikation und der Geschlechtsschatzung liegt. Anschliesend wird die Nutzung dieser Informationen anhand der Dialogfuhrung eines interaktiven Shopping-Assistenten diskutiert.

Towards an attentive robotic dialog partner

This paper describes a system developed for a mobile service robot which detects and tracks the position of a users face in 3D-space using a vision (skin color) and a sonar based component. To make the skin color detection robust under varying illumination conditions, it is supplied with an automatic white balance algorithm. The hypothesis of the users position is used to orient the robots head towards the current user allowing it to grab high resolution images of his face suitable for verifying the hypothesis and for extracting additional information.

Multimodale Mensch-Maschine-Interaktion für Servicerobotik-Systeme

Die Frage der Mensch-Roboter-Interaktion wird fur zukunftige erfolgreiche Applikationen von Servicerobotern eine wesentliche, wenn nicht die zentrale Rolle spielen. Vor diesem Hintergrund beschreibt der vorliegende Beitrag ein Konzept zur multimodalen Mensch-Maschine-Kommunikation und dessen Realisierungsstand anhand eines konkreten Einsatzszenarios, der Entwicklung eines intelligenten, interaktiven und mobilen Informationskiosks im Baumarkt. Obwohl sich das vorgestellte Konzept an den konkreten Erfordernissen dieses Szenarios orientiert, stellt es einen generischen Ansatz dar, der sich auf eine Vielzahl weiterer Applikationen ubertragen lasst.